U.S. Department of Energy

Pacific Northwest National Laboratory

Jason McDermott

Jason McDermott
Professional Title: 
Scientist & Team Lead
Phone Number: 
(509) 372-4360

Dr. Jason McDermott, senior research scientist, has extensive research experience in molecular and structural virology and data resource design, data integration and prediction of biological networks, bridging experimental and computational biology. Currently, his research interests include data integration of high-throughput ‘omics data for biomarker discovery, developing systems biology models in a number of systems focusing on host-pathogen interactions, characterizing phylogenetic and functional relationships in complex eukaryotic microbial communities, and using network inference and topology to characterize organism-level phenotypes.

  • Post-doctoral, University of Washington, Bioinformatics, 2006
  • Ph.D., Oregon Health & Science University, Structural Virology, 2000
  • B.A. Reed College, Biology, 1993
  • 1997 Sears Fellowship Award (OHSU)
  • 1998 Tartar Fellowship Award (OHSU)
  • 2008 Analytics Challenge Winner (Supercomputing 2008)
Research Interests: 

Cancer biology and pathway analysis

Cancer is a pathway-centric disease. The emergence of high-throughput molecular profiling methods such as transcriptomics and proteomics has revolutionized our ability to interrogate signaling and functional pathways involved in cancer. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) is an NCI program tasked with proteomic characterization of tumors from The Cancer Genome Atlas (TCGA). I have worked on our PNNL-led CPTAC project to characterize nearly 200 high-grade serous ovarian cancer tumors by proteomics and phosphoproteomics. I have developed several methods for integration of data types to determine pathway activity, and pathway-centric survival prediction methods. This work builds on my extensive experience in this area from other domains. In addition, I have actively participated in the consortium, which holds bi-weekly teleconferences and meets in person twice per year, serving as the chair of the biology working group and the chair of the data analysis working group.

Biological network analysis and predictive modeling

Networks are an abstract representation of biological systems that have been shown to be very useful for gaining biological insight and forming hypotheses. Many network studies work with experimentally derived networks of protein-protein interactions, regulatory interactions, or metabolic interactions, which are sparse and expensive to produce. I extended topological analysis of biological networks to networks inferred from high-throughput data. These networks are easy to generate from compendia of transcriptomics, proteomics, or metabolomics data. I showed for a number of systems that topologically important locations (high centrality and high degree proteins, e.g.) in these inferred networks are more likely to be important for functioning of the system as evaluated by a number of different phenotypes. I extended this work to develop and extend methods for inference of dynamic predictive models that could be used to simulate the behavior of a system over time and predict important nodes (proteins or genes) that are postulated to be gatekeepers for transitions between different system states.

Integrative omics for biomarker discovery

The field of biomarker discovery has been greatly expanded by the advent of high-throughput methods for data acquisition such as transcriptomics, proteomics, and metabolomics. However, this rapid advance has driven the need for novel methods to integrate disparate types of data to identify biomarkers that are robust from study-to-study. We have found in the studies listed below and others, that integration of different data types can improve phenotypic predictions dramatically. We have also developed methods to make better use of data coming from the proteomics and metabolomics platforms. Finally, we’ve developed approaches for integrating high-throughput data with existing knowledge about the biological problems to improve the robustness and reproducibility of the resulting predictions and insights. I have worked very closely with biologists (e.g. Dr. Rodland), statisticians (e.g. Dr. Webb-Robertson), and mass-spectrometrists (e.g. Dr. Metz) to develop the ideas for these approaches, implement methods in software, and analyze integrated data to provide predictions and biological insight. An important component that I have been working on recently is reproducibility and robustness, which pervades the rest of my work as well.

Computational prediction of problematic protein families

Prediction of protein functions has been accomplished by exploiting evolutionary similarities between sequences, which can be used to map functions to uncharacterized protein sequences. This has been and continues to be a very effective approach, but it fails for important protein functions that have diverse sequences that can not be connected using existing methods or where the sequences are highly related, but specific function can’t be assigned. I have used machine learning methods to produce one of the first computational methods to predict type III secreted bacterial effectors, which have diverse sequences. This has spawned a series of related papers, both improvements on type III secreted effector predictions and for prediction of other types of secreted effectors such as type IV substrates. Additionally, the algorithm, for which I have released a publically-accessible webserver, has been used many times and the results have been included in studies by collaborators and others. This work has recently been extended to predict multi-drug resistance transporters, which are related by sequence in very large families of transporters, but for which substrate specificity remains unknown. I originally worked with Dr. Fred Heffron to develop this approach and validate results. I have done all the algorithm development and participated in experimental study design for the validation and related experimental studies. In addition I led an effort to experimentally characterize the structural properties of secretion signal peptides.

Systems biology of infectious disease

The interactions between pathogen and host are very important to understand from a human disease perspective, but are generally poorly understood. The advent of high-throughput methods has allowed gathering of large amounts of data on these systems. However, methods to utilize this data in to develop systems biology models that can provide actionable hypotheses is an area of great need. I have worked with several NIAID-funded projects to develop regulatory networks of Salmonella Typhimurium, Yersinia pestis, and host response to HCV, influenza, and SARS viruses. These studies revealed important aspects of each host-pathogen interaction allowing identification, and subsequent validation, of critical genes and proteins involved in virulence or response to pathogens.




  • McDermott JE, M Partridge, and Y Bromberg. 2018. "Ten Simple Rules for Drawing Scientific Comics." PLoS Computational Biology 14(1):Article No. e1005845. doi:10.1371/journal.pcbi.1005845
  • Moghieb A, Clair G, Mitchell H, Kitzmiller J, Zink E, Kim Y, Petyuk V, Shukla A, Moore R, Metz TO, Carson J, McDermott J, Corley R, Whitsett J, Charles A. 2018. Time-resolved Proteome and Metabolome Profiling of Normal Lung Development. Am J Physiol Lung Cell Mol Physiol. 315(1):L11-L24. doi: 10.1152/ajplung.00316.2017
  • McClure RS, Overall CO, Charania M, Hill EA, Bernstein HC, McDermott JE, Beliaev A. 2018. Species-specific Transcriptomic Network Inference of Interspecies Interactions in Microbial Communities. ISME 12(8):2011-2023. doi: 10.1038/s41396-018-0145-6
  • Hosseini MH, Kurtz SE, Abdelhamed S, Mahmood S, Davare, MA, Kaempf A, Elferich J, McDermott JE, Liu T, Payne SH, Shinde U, Rodland KD, Mori M, Druker BJ, Singer JK, Agarwal A. 2018. Inhibition of interleukin-1 receptor-associated kinase-1 is a therapeutic strategy for acute myeloid leukemia subtypes. Leukemiaepub. doi: 10.1038/s41375-018-0112-2

  • Duhen T, Duhen R, Montler R, Moses J, Moudgil T, de Miranda NF, Goodall CP, Blair TC, Fox BA, McDermott JE, Chang SC, Grunkemeier G, Leidner R, Bell RB, Weinberg AD. 2018. Co-expression of CD39 and CD103 identifies tumor-reactive CD8 T cells in human solid tumors. Nature Communications 9(1):2724. doi: 10.1038/s41467-018-05072-0

  • Sharpnack MF, Ranbaduge N, Srivastava A, Cerciello F, Codreanu SG, Liebler DC, Mascaux C, Miles WO, Morris R, McDermott JE, Sharpnack JL, Amann J, Maher CA, Machiraju R, Wysocki VH, Govindan R, Mallick P, Coombes KR, Huang K, Carbone DP. 2018. Proteogenomic Analysis of Surgically Resected Lung Adenocarcinoma. J Thorac Oncol. 2018 Jul 11. pii: S1556-0864(18)30784-6. doi: 10.1016/j.jtho.2018.06.025

  • Colby SM, McClure RS, Overall CC, Renslow RS, McDermott JE. Improving network inference and functional module identification using resampling methods. BMC Bioinformatics19(1):376


  • McDermott JE. 2017. "Working Life: Drawing Connections." Science 356(6343):1202. doi:10.1126/science.356.6343.1202
  • Maier TV, M Lucio, LH Lee, N VerBerkmoes, CJ Brislawn, J Bernhardt, R Lamendella, JE McDermott, N Bergeron, SS Heinzmann, J Morton, A Gonzalez, G Ackermann, R Knight, K Riedel, R Krauss, P Schmitt-Kopplin, and JK Jansson. 2017. "Impact of Dietary Resistant Starch on the Human Gut Microbiome, Metaproteome and Metabolome." mBio 8(5):Article No. e01343-17.  doi:10.1128/mBio.01343-17
  • Wang J, Z Ma, SA Carr, P Mertins, H Zhang, Z Zhang, DW Chan, MJ Ellis, R Townsend, RD Smith, JE McDermott, X Chen, AG Paulovich, E Boja, M Mesri, C Kinsinger, H Rodriguez, KD Rodland, D Liebler, and B Zhang. 2017. "Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction." Molecular & Cellular Proteomics. MCP 16(1):121-134.  doi:10.1074/mcp.M116.060301


  • McDermott JE, HD Mitchell, L Gralinski, AJ Eisfeld, L Josset, A Bankhead, G Neumann, SC Tilton, A Schafer, C Li, S Fan, SK Mcweeney, R Baric, MG Katze, and KM Waters. 2016. "The Effect of inhibition of PP1 and TNFa signaling on pathogenesis of SARS coronavirus." BMC Systems Biology 10(1):93.  doi:10.1186/s12918-016-0336-6
  • Bernstein HC, RS McClure, EA Hill, LM Markillie, WB Chrisler, MF Romine, JE McDermott, MC Posewitz, DA Bryant, A Konopka, JK Fredrickson, and AS Beliaev. 2016. "Unlocking the Constraints of Cyanobacterial Productivity: Acclimations Enabling Ultrafast Growth." mBio 7(4):Article No. e00949-16.  doi:10.1128/mBio.00949-16
  • McClure RS, CC Overall, JE McDermott, EA Hill, LM Markillie, LA McCue, RC Taylor, M Ludwig, DA Bryant, and AS Beliaev. 2016. "Network Analysis of Transcriptomics Expands Regulatory Landscapes in Synechococcus sp. PCC 7002." Nucleic Acids Research 44(18):8810-8825.  doi:10.1093/nar/gkw737
  • Mitchell HD, LM Markillie, WB Chrisler, MJ Gaffrey, D Hu, CJ Szymanski, Y Xie, ES Melby, A Dohnalkova, RC Taylor, EK Grate, SK Cooley, JE McDermott, A Heredia-Langner, and G Orr. 2016. "Cells Respond to Distinct Nanoparticle Properties with Multiple Strategies as Revealed by Single-Cell RNA-Seq." ACS Nano 10(11):10173-10185. doi:10.1021/acsnano.6b05452
  • Oxford KL, JP Wendler, JE McDermott, RA White, III, JD Powell, JM Jacobs, JN Adkins, and KM Waters. 2016. "The Landscape of Viral Proteomics and Its Potential to Impact Human Health." Expert Review of Proteomics 13(6):579-591.  doi:10.1080/14789450.2016.1184091
  • Shi T, M Niepel, JE McDermott, Y Gao, CD Nicora, WB Chrisler, LM Markillie, VA Petyuk, RD Smith, KD Rodland, P Sorger, W Qian, and HS Wiley. 2016. "Conservation of Protein Abundance Patterns Reveals the Regulatory Architecture of the of the EGFR-MAPK Pathway." Science Signaling 9(436):rs6.  doi:10.1126/scisignal.aaf0891
  • Tabb DL, X Wang, SA Carr, K Clauser, P Mertins, MC Chambers, JD Holman, J Wang, B Zhang, LJ Zimmerman, X Chen, H Gunawardena, S Davies, M Ellis, S Li, R Townsend, E Boja, K Ketchum, C Kinsinger, M Mesri, H Rodriguez, T Liu, S Kim, JE McDermott, SH Payne, VA Petyuk, KD Rodland, RD Smith, F Yang, DW Chan, B Zhang, H Zhang, Z Zhang, JY Zhou, and D Liebler. 2016. "Reproducibility of differential proteomic technologies in CPTAC fractionated xenografts." Journal of Proteome Research 15(3):691-706. doi:10.1021/acs.jproteome.5b00859
  • Zhang H, T Liu, Z Zhang, SH Payne, B Zhang, JE McDermott, JY Zhou, VA Petyuk, L Chen, D Ray, S Sun, F Yang, L Chen, J Wang, P Shah, SW Cha, P Aiyetan, S Woo, Y Tian, MA Gritsenko, TRW Clauss, C Choi, ME Monroe, SN Thomas, S Nie, C Wu, RJ Moore, KH Yu, DL Tabb, D Fenyo, V Bafna, Y Wang, H Rodriguez, E Boja, T Hiltket, R Rivers, LJ Sokoll, H Zhu, IM Shih, L Cope, A Pandey, B Zhang, M Snyder, D Levine, RD Smith, DW Chan, and KD Rodland. 2016. "Integrated proteogenomic characterization of human high grade serous ovarian cancer." Cell 166(3):755-765.  doi:10.1016/j.cell.2016.05.069


  • Li J, CC Overall, ES Nakayasu, AS Kidwai, MB Jones, R Johnson, NT Nguyen, JE McDermott, C Ansong, F Heffron, E Cambronne, and JN Adkins. 2015. "Analysis of the Salmonella regulatory network suggests involvement of SsrB and H-NS in sE-regulated SPI-2 gene expression." Frontiers in Microbiology 6:Artcle No. 27.  doi:10.3389/fmicb.2015.00027
  • Li J, CC Overall, R Johnson, MB Jones, JE McDermott, F Heffron, JN Adkins, and E Cambronne. 2015. "ChIP-Seq Analysis of the s E Regulon of Salmonella enterica Serovar Typhimurium Reveals New Genes Implicated in Heat Shock and Oxidative Stress Response." PLoS One 10(9):Article No. e0138466.  doi:10.1371/journal.pone.0138466
  • Li J, ES Nakayasu, CC Overall, R Johnson, AS Kidwai, JE McDermott, C Ansong, F Heffron, E Cambronne, and JN Adkins. 2015. "Global analysis of Salmonella alternative sigma factor E on protein translation." Journal of Proteome Research 14(4):1716-1726. doi:10.1021/pr5010423
  • Vartanian KB, HD Mitchell, S Stevens, VK Conrad, JE McDermott, and M Stenzel-Poore. 2015. "CpG preconditioning regulates miRNA expression that modulates genomic reprogramming associated with neuroprotection against ischemic injury." Journal of Cerebral Blood Flow and Metabolism 35(2):257-266.  doi:10.1038/jcbfm.2014.193
  • Webb-Robertson BJM, HK Wiberg, MM Matzke, JN Brown, J Wang, JE McDermott, RD Smith, KD Rodland, TO Metz, JG Pounds, and KM Waters. 2015. "Review, Evaluation, and Discussion of the Challenges of Missing Value Imputation for Mass Spectrometry-Based Label-Free Global Proteomics." Journal of Proteome Research 14(5):1993-2001. doi:10.1021/pr501138h


  • McDermott JE, Y Huang, B Zhang, H Xu, and Z Zhao. 2014. "Integrative Genomics and Computational Systems Medicine." BioMed Research International 2014:Article No. 945253. doi:10.1155/2014/945253
  • Aevermann B, BE Pickett, S Kumar, EB Klem, S Agnihothram, PS Askovich, A Bankhead, M Bolles, V Carter, JH Chang, TRW Clauss, P Dash, AH Diercks, AJ Eisfeld, AL Ellis, S Fan, MT Ferris, L Gralinski, R Green, MA Gritsenko, M Hatta, RA Heegel, JM Jacobs, S Jeng, L Josset, SM Kaiser, S Kelly, GL Law, C Li, J Li, C Long, ML Luna, MM Matzke, JE McDermott, V Menachery, TO Metz, HD Mitchell, ME Monroe, G Navarro, G Neumann, RL Podyminogin, SO Purvine, C Rosenberger, CJ Sanders, AA Schepmoes, AK Shukla, A Sims, P Sova, VC Tam, N Tchitchek, PG Thomas, SC Tilton, AL Totura, J Wang, BJM Webb-Robertson, J Wen, JM Weiss, F Yang, B Yount, Q Zhang, SK Mcweeney, RD Smith, KM Waters, Y Kawaoka, R Baric, A Aderem, MG Katze, and RH Scheuermann. 2014. "A Comprehensive Collection of Systems Biology Data Characterizing the Host Response to Viral Infection." Scientific Data 1:Article No. 140033.  doi:10.1038/sdata.2014.33
  • Kang SH, SH Kahan, JE McDermott, NS Flann, and I Shmulevich. 2014. "Biocellion: Accelerating Computer Simulation of Multicellular Biological System Models." Bioinformatics 30(21):3101-3108.  doi:10.1093/bioinformatics/btu498
  • Webb-Robertson BJM, MM Matzke, S Datta, SH Payne, J Kang, LM Bramer, CD Nicora, AK Shukla, TO Metz, KD Rodland, RD Smith, MF Tardiff, JE McDermott, JG Pounds, and KM Waters. 2014. "Bayesian Proteoform Modeling Improves Protein Quantification of Global Proteomic Measurements." Molecular and Cellular Proteomics 13(12):3639-3646. doi:10.1074/mcp.M113.030932


  • Kim YM, B Schmidt, AS Kidwai, MB Jones, BL Deatherage, HM Brewer, HD Mitchell, BO Palsson, JE McDermott, F Heffron, RD Smith, SN Peterson, C Ansong, DR Hyduke, TO Metz, and JN Adkins. 2013. "Salmonella Modulates Metabolism During Growth under Conditions that Induce Expression of Virulence Genes." Molecular Biosystems 9(6):1522-1534. doi:10.1039/C3MB25598K
  • Ansong C, AC Rutledge, HD Mitchell, S Chauhan, MB Jones, YM Kim, K Mcateer, BL Deatherage, JL DuBois, HM Brewer, BC Frank, JE McDermott, TO Metz, SN Peterson, RD Smith, VL Motin, and JN Adkins. 2013. "A multi-omic systems approach to elucidating Yersinia virulence mechanisms." Molecular Biosystems 9(1):44-54.  doi:10.1039/C2MB25287B 
  • Hafen RP, LJ Gosink, JE McDermott, KD Rodland, K Kleese-Van Dam, and WS Cleveland. 2013. "Trelliscope: A System for Detailed Visualization in Analysis of Large Complex Data." In IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV 2013), October 13-14, 2013, Atlanta, Georgia, pp. 105-112.  IEEE, Piscataway, NJ. doi:10.1109/LDAV.2013.6675164
  • Matzke MM, JN Brown, MA Gritsenko, TO Metz, JG Pounds, KD Rodland, AK Shukla, RD Smith, KM Waters, JE McDermott, and BJM Webb-Robertson. 2013. "A Comparative Analysis of Computational Approaches to Relative Protein Quantification Using Peptide Peak Intensities in Label-free LC-MS Proteomics Experiments." Proteomics 13(3-4):493-503. doi:10.1002/pmic.201200269
  • McDermott JE, J Wang, HD Mitchell, BJM Webb-Robertson, RP Hafen, JA Ramey, II, and KD Rodland. 2013. "Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data." Expert Opinion on Medical Diagnostics 7(1):37-51.  doi:10.1517/17530059.2012.718329
  • Mitchell HD, AJ Eisfeld, A Sims, JE McDermott, MM Matzke, BJM Webb-Robertson, SC Tilton, N Tchitchek, L Josset, C Li, AL Ellis, JH Chang, RA Heegel, ML Luna, AA Schepmoes, AK Shukla, TO Metz, G Neumann, A Benecke, RD Smith, R Baric, Y Kawaoka, MG Katze, and KM Waters. 2013. "A Network Integration Approach to Predict Conserved Regulators Related to Pathogenicity of Influenza and SARS-CoV Respiratory Viruses." PLoS One 8(7):e69374. doi:10.1371/journal.pone.0069374
  • Niemann G, RN Brown, IT Mushamiri, NT Nguyen, R Taiwo, A Stufkens, RD Smith, JN Adkins, JE McDermott, and F Heffron. 2013. "RNA Type III Secretion Signals that require Hfq." Journal of Bacteriology 195(10):2119-2125.  doi:10.1128/JB.00024-13
  • Sanfilippo AP, JN Haack, JE McDermott, SL Stevens, and M Stenzel-Poore. 2013. "Modeling Emergence in Neuroprotective Regulatory Networks." In Complex Sciences: Second International Conference COMPLEX 2012, December 5-7, 2012, Santa Fe, New Mexico. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 126, ed. K Glass, et al, pp. 291-302.  Springer, New York, NY.  doi:10.1007/978-3-319-03473-7_26
  • Wang J, BJM Webb-Robertson, MM Matzke, SM Varnum, JN Brown, RM Riensche, JN Adkins, JM Jacobs, JR Hoidal, MB Scholand, JG Pounds, MR Blackburn, KD Rodland, and JE McDermott. 2013. "A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification." Disease Markers 35(5):513-523.  doi:10.1155/2013/613529
  • Webb-Robertson BJM, MM Matzke, TO Metz, JE McDermott, J Walker, KD Rodland, JG Pounds, and KM Waters. 2013. "Sequential Projection Pursuit Principal Component Analysis - Dealing with Missing Data Associated with New -Omics Technologies." BioTechniques 54(3):165-168. 
  • Zhang B, Y Huang, JE McDermott, RH Posey, H Xu, and Z Zhao. 2013. "Interdisciplinary Dialogue for Education, Collaboration, and Innovation: Intelligent Biology and Medicine In and Beyond 2013." BMC Genomics 14(Suppl 8):Article No. S1.  doi:10.1186/1471-2164-14-S8-S1


  • McDermott JE, KB Vartanian, HD Mitchell, SL Stevens, AP Sanfilippo, and M Stenzel-Poore. 2012. "Identification and Validation of Ifit1 as an Important Innate Immune Bottleneck ." PLoS One 7(6):e36465.  doi:10.1371/journal.pone.0036465
  • Acquaah-Mensah G, D Malhotra, M Vulimiri, JE McDermott, and S Biswal. 2012. " Suppressed Expression of T-Box Transcription Factors is Involved in Senescence in Chronic Obstructive Pulmonary Disease." PLoS Computational Biology 8(7):e1002597. doi:10.1371/journal.pcbi.1002597
  • Archuleta MN, JE McDermott, JS Edwards, and H Resat. 2012. "An Adaptive Coarse Graining Method for Signal Transduction in Three-Dimensions." FUNDAMENTA INFORMATICAE 118(4):371-384.  doi:10.3233/FI-2012-720
  • Diamond DL, A Krasnoselski, KE Burnum, ME Monroe, BJM Webb-Robertson, JE McDermott, MM Yeh, JF Golib-Dzib, N Susnow, S Strom , S Proll, S Belisle, DE Purdy, A Rasmussen, KA Walters, JM Jacobs, MA Gritsenko, DG Camp, II, R Bhattacharya, JD Perkins, RL Carithers, IW Liou, AM Larson, A Benecke, KM Waters, RD Smith, and MG Katze. 2012. "Proteome and Computational Analyses Reveal New Insights into the Mechanisms of Hepatitis C Virus Mediated Liver Disease Posttransplantation." Hepatology 56(1):28-38. doi:10.1002/hep.25649
  • McDermott JE, DL Diamond, CD Corley, A Rasmussen, MG Katze, and KM Waters. 2012. "Topological Analysis of Protein Co-Abundance Networks Identifies Novel Host Targets Important for HCV Infection and Pathogenesis ." BMC Systems Biology 6(1):28. doi:10.1186/1752-0509-6-28
  • McDermott JE, KD Jarman, RC Taylor, MJ Lancaster, H Shankaran, KB Vartanian, SL Stevens, M Stenzel-Poore, and AP Sanfilippo. 2012. "Modeling Dynamic Regulatory Processes in Stroke." PLoS Computational Biology 8(10):e1002722.  doi:10.1371/journal.pcbi.1002722


  • McDermott JE, AL Corrigan, ES Peterson, CS Oehmen, G Niemann, E Cambronne, D Sharp, JN Adkins, R Samudrala, and F Heffron. 2011. "Computational prediction of type III and IV secreted effectors in Gram-negative bacteria ." Infection and Immunity 79(1):23-32. doi:10.1128/IAI.00537-10
  • McDermott JE, CS Oehmen, LA McCue, EA Hill, DM Choi, J Stockel, ML Liberton, HB Pakrasi, and LA Sherman. 2011. "A Model of Cyclic Transcriptomic Behavior in Cyanobacterium Cyanothece sp. ATCC 51142." Molecular Biosystems 7(8):2407-2418. doi:10.1039/C1MB05006K
  • McDermott JE, H Yoon, ES Nakayasu, TO Metz, DR Hyduke, AS Kidwai, BO Palsson, JN Adkins, and F Heffron. 2011. "Technologies and Approaches to Elucidate and Model the Virulence Program of Salmonella." Frontiers in Microbiology 2:121. doi:10.3389/fmicb.2011.00121
  • McDermott JE, MN Archuleta, BD Thrall, JN Adkins, and KM Waters. 2011. "Controlling the Response: Predictive Modeling of a Highly Central, Pathogen-Targeted Core Response Module in Macrophage Activation." PLoS One 6(2):e14673. doi:10.1371/journal.pone.0014673
  • McDermott JE, MN Costa, SL Stevens, M Stenzel-Poore, and AP Sanfilippo. 2011. "DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS." In Biocomputing 2011: Proceedings of the Pacific Symposium on Biocomputing, January 3-7, 2011, Kohala Coast, Hawaii, ed. RB Altman, et al, pp. 314-25.  World Scientific, London, United Kingdom.  doi:10.1142/9789814335058_0033
  • McDermott JE, P Braun, RA Bonneau, and DR Hyduke. 2011. "MODELING HOST-PATHOGEN INTERACTIONS: COMPUTATIONAL BIOLOGY AND BIOINFORMATICS FOR INFECTIOUS DISEASE RESEARCH (Session introduction)." In Pacific Syposium on Biocomputing 2012, January 3-7, 2012, Honolulu, Hawaii, vol. 17, pp. 283-286.  Stanford University, Stanford, CA. 
  • Aderem A, JN Adkins, C Ansong, J Galagan, S Kaiser, MJ Korth, GL Law, JE McDermott, S Proll, C Rosenberger, G Schoolnik, and MG Katze. 2011. "A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm." mBio 2(1):Article No. e00325.  doi:10.1128/mBio.00325-10
  • Heffron F, G Niemann, H Yoon, AS Kidwai, RN Brown, JE McDermott, RD Smith, and JN Adkins. 2011. "Salmonella-secreted Virulence Factors." Chapter 10 in Salmonella: From Genome to Function, ed. S Porwollik, pp. 187-223.  Caister Academic Press, Norfolk, United Kingdom. 
  • McDermott JE, H Shankaran, AJ Eisfeld, S Belisle, G Neumann, C Li, SK Mcweeney, CL Sabourin, Y Kawaoka, MG Katze, and KM Waters. 2011. "Conserved Host Response to Highly Pathogenic Avian Influenza Virus Infection in Human Cell Culture, Mouse and Macaque Model Systems." BMC Systems Biology 5:Article No. 190.  doi:10.1186/1752-0509-5-190
  • Niemann G, RN Brown, JK Gustin, A Stufkens, AS Shaikh-Kidwai, J Li, JE McDermott, HM Brewer, AA Schepmoes, RD Smith, JN Adkins, and F Heffron. 2011. "Discovery of Novel Secreted Virulence Factors from Salmonella enterica Serovar Typhimurium by Proteomic Analysis of Culture Supernatants." Infection and Immunity 79(1):33-43. doi:10.1128/IAI.00771-10
  • Rasmussen A, DL Diamond, JE McDermott, X Gao, TO Metz, MM Matzke, V Carter, S Belisle, MJ Korth, KM Waters, RD Smith, and MG Katze. 2011. "Systems Virology Identifies a Mitochondrial Fatty Acid Oxidation Enyzme, Dodecenoyl Coenzyme A Delta Isomerase, Required for Hepatitis C Virus Replication and Likely Pathogenesis." Journal of Virology 85(22):11646-11654.  doi:10.1128/JVI.05605-11
  • Taylor RC, AP Sanfilippo, JE McDermott, RL Baddeley, RM Riensche, RS Jensen, M Verhagen, and J Pustejovsky. 2011. "Enriching regulatory networks by bootstrap learning using optimised GO-based gene similarity and gene links mined from PubMed abstracts." International Journal of Computational Biology and Drug Design 4(1):56-82. doi:10.1504/IJCBDD.2011.038657
  • Yoon H, C Ansong, JE McDermott, MA Gritsenko, RD Smith, F Heffron, and JN Adkins. 2011. "Systems analysis of multiple regulator perturbations allows discovery of virulence factors in Salmonella ." BMC Systems Biology 5:Article No. 100.  doi:10.1186/1752-0509-5-100


  • McDermott JE, AP Sanfilippo, RC Taylor, RL Baddeley, RM Riensche, and RS Jensen. 2010. "An Integrated Approach to Predictive Genomic Analytics." In Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology, pp. 390-393.  Association for Computing Machinery, New York, NY. doi:10.1145/1854776.1854837
  • Buchko GW, G Niemann, ES Baker, ME Belov, RD Smith, F Heffron, JN Adkins, and JE McDermott. 2010. "A multi-pronged search for a common structural motif in the secretion signal of Salmonella enterica serovar Typhimurium type III effector proteins." Molecular Biosystems 6(12):2448-2458.  doi:10.1039/c0mb00097c
  • Diamond DL, AJ Syder, JM Jacobs, CM Sorensen, KA Walters, S Proll, JE McDermott, MA Gritsenko, Q Zhang, R Zhao, TO Metz, DG Camp, II, KM Waters, RD Smith, CM Rice, and MG Katze. 2010. "Temporal Proteome and Lipidome Profiles Reveal HCV-Associated Reprogramming of Hepatocellular Metabolism and Bioenergetics ." PLoS Pathogens 6(1):Art. No. e1000719.  doi:10.1371/journal.ppat.1000719
  • Lawrence P, W Kittichotirat, JE McDermott, and RE Bumgarner. 2010. "A Three-way Comparative Genomic Analysis of Mannheimia haemolytica Isolates." BMC Genomics 11:535.  doi:10.1186/1471-2164-11-535
  • Lawrence P, W Kittichotirat, RE Bumgarner, JE McDermott, D Herndon, DP Knowles, and S Srikumaran. 2010. "Genome sequences of Mannheimia haemolytica serotype A2: ovine and bovine isolates." Journal of Bacteriology 192(4):1167-1168.  doi:10.1128/JB.01527-09
  • McDermott JE, MN Costa, DB Janszen, M Singhal, and SC Tilton. 2010. "Separating the Drivers from the Driven: Integrative Network and Pathway Approaches Aid Identification of Disease Biomarkers from High-Throughput Data." Disease Markers 28(4):253-266. 
  • Taylor RC, AP Sanfilippo, JE McDermott, RL Baddeley, RM Riensche, RS Jensen, and M Verhagen. 2010. "Learning Biological Networks via Bootstrapping with Optimized GO-based Gene Similarity." In Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology, pp. 515-519.  Association for Computing Machinery, New York, NY.  doi:10.1145/1854776.1854875
  • Wang J, J Zhang, R Li, H Zheng, J Li, Y Zhang, H Li, P Ni, S Li, S Li, J Wang, D Liu, JE McDermott, R Samudrala, S Liu, J Wang, H Yang, J Yu, and GKS Wong. 2010. "Evolutionary transients in the rice transcriptome." Genomics, Proteomics & Bioinformatics 8(4):211-228. doi:10.1016/S1672-0229(10)60023-X


  • Cannon WR, BJM Webb-Robertson, AR Willse, M Singhal, LA McCue, JE McDermott, RC Taylor, KM Waters, and CS Oehmen. 2009. "An Integrative Computational Framework for Hypotheses-Driven Systems Biology Research in Proteomics and Genomics." Chapter 4 in Computational and Systems Biology: Methods and Applications, pp. 63-85.  Research Signpost, Trivandrum, India. 
  • McDermott JE, J Wang, J Yu, GKS Wong, and R Samudrala. 2009. "Prediction and Annotation of Plant Protein Interaction Networks." Chapter 9 in Plant Genomics and Bioinformatics, ed. GP Rao, C Wagner, RK Singh and ML Sharma, pp. 207-238.  Studium Press LLC, Houston, TX. 
  • McDermott JE, R Samudrala, RE Bumgarner, K Montogomery, and R Ireton. 2009. Computational Systems Biology.  Humana Press, Totowa, NJ. 
  • McDermott JE, RC Taylor, H Yoon, and F Heffron. 2009. "Bottlenecks and Hubs in Inferred Networks Are Important for Virulence in Salmonella typhimurium." Journal of Computational Biology 16(2):169-180.  doi:10.1089/cmb.2008.04TT
  • Frazier Z, JE McDermott, M Guerquin, and R Samudrala. 2009. "Computational representation of biological systems." Chapter 53 in Computational Systems Biology, Methods in Molecular Biology, vol. 541, pp. 535-550.  Humana Press, Totowa, NJ. 
  • Guerquin M, JE McDermott, Z Frazier, and R Samudrala. 2009. "The Bioverse API and Web Application." Chapter 22 in Computational Systems Biology, Methods in Molecular Biology, vol. 541, pp. 511-534.  Humana Press, Totowa, NJ. 
  • Rashid I, JE McDermott, and R Samudrala. 2009. "Inferring molecular interactions pathways from eQTL data." Chapter 10 in Computational Systems Biology, Methods in Molecular Biology, vol. 541, pp. 211-224.  Humana Press, Totowa, NJ. 
  • Samudrala R, F Heffron, and JE McDermott. 2009. "Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems." PLoS Pathogens 5(4):,
  • Sanfilippo AP, RL Baddeley, N Beagley, JE McDermott, RM Riensche, RC Taylor, and B Gopalan. 2009. "Using the Gene Ontology to Enrich Biological Pathways." International Journal of Computational Biology and Drug Design 2(3):221-235. doi:10.1504/IJCBDD.2009.030114
  • Shi L, C Ansong, HS Smallwood, LM Rommereim, JE McDermott, HM Brewer, AD Norbeck, RC Taylor, JK Gustin, F Heffron, RD Smith, and JN Adkins. 2009. "Proteome of Salmonella enterica serotype Tyhimurium Grown in Low Mg2+/pH Medium." Journal of Proteomics and Bioinformatics 2(9):388-397.  doi:10.4172/jpb.1000099
  • Shi L, C Ansong, HS Smallwood, LM Rommereim, JE McDermott, HM Brewer, AD Norbeck, RC Taylor, JK Gustin, F Heffron, RD Smith, and JN Adkins. 2009. "Proteome of Salmonella Enterica SerotypeTyphimurium Grown in a Low Mg2+/pH Medium." Journal of Proteomics and Bioinformatics 2(9):388-397.  doi:10.4172/jpb.1000099
  • Shi L, SM Chowdhury, HS Smallwood, H Yoon, HM Mottaz-Brewer, AD Norbeck, JE McDermott, TRW Clauss, F Heffron, RD Smith, and JN Adkins. 2009. "Proteomic Investigation of the Time Course Responses of RAW 264.7 Macrophages to Infection with Salmonella enterica." Infection and Immunity 77(8):3227-3233.  doi:10.1128/IAI.00063-09
  • Taylor RC, M Singhal, DS Daly, JM Gilmore, WR Cannon, KO Domico, AM White, DL Auberry, KJ Auberry, BS Hooker, GB Hurst, JE McDermott, WH McDonald, DA Pelletier, DA Schmoyer, and HS Wiley. 2009. "An analysis pipeline for the inference of protein-protein interaction networks." International Journal of Data Mining and Bioinformatics 3(4) (Sp. Iss. SI):409-430. 
  • Taylor RC, M Singhal, JB Weller, S Khoshnevis, L Shi, and JE McDermott. 2009. "A Network Inference Workflow Applied to Virulence-Related Processes in Salmonella typhimurium ." In Annals of the New York Academy of Sciences, vol. 1158, pp. 143-158.  PubMed, New York, NY. 
  • Toepel J, JE McDermott, T Summerfield, and LA Sherman. 2009. "Transcriptional analysis of the unicellular, diazotrophic cyanobacterium Cyanothece sp. ATCC 51142 grown under short day/night cycles." Journal of Phycology 45(3):610-620. 
  • Webb-Robertson BJM, LA McCue, N Beagley, JE McDermott, DS Wunschel, SM Varnum, JZ Hu, NG Isern, GW Buchko, K Mcateer, JG Pounds, SJ Skerret, D Liggitt, and CW Frevert. 2009. "A Bayesian Integration Model of High-Throughput Proteomics and Metabolomics Data for Improved Early Detection of Microbial Infections." In Pacific Symposium on Biocomputing, vol. 14, pp. 451-463.  World Scientific Publishing Co., Singapore, Singapore. 
  • Wichadakul D, JE McDermott, and R Samudrala. 2009. "Prediction and integration of regulatory and protein-protein interactions." Chapter 6 in Computational Systems Biology, Methods in Molecular Biology, vol. 541, pp. 101-144.  Humana Press, Totowa, NJ. 
  • Yoon H, JE McDermott, S Porwollik, M Mcclelland, and F Heffron. 2009. "Coordinated Regulation of Virulence during Systemic Infection of Salmonella enterica serovar Typhimurium." PLoS Pathogens 5(2):1-16. 


  • McDermott JE, and R Samudrala. 2008. "Bioinformatic characterization of plant networks." In Proceedings of the Asia Pacific Conference on Plant Tissue Culture and Agrobiotechnology (APaCPA) 2007.  Aimst University, Bedong, Malaysia. 
  • Ansong C, H Yoon, AD Norbeck, JK Gustin, JE McDermott, HM Mottaz, J Rue, JN Adkins, F Heffron, and RD Smith. 2008. "Proteomics Analysis of the Causative Agent of Typhoid Fever." Journal of Proteome Research 7(2):546-557.  doi:10.1021/pr070434u
  • Gorton I, CS Oehmen, and JE McDermott. 2008. "It Takes Glue to Tango: MeDICi integration framework creates data-intensive computing pipeline." Scientific Computing 25(7):16-24. 


  • Taylor RC, M Singhal, DS Daly, KO Domico, AM White, DL Auberry, KJ Auberry, BS Hooker, GB Hurst, JE McDermott, WH McDonald, DA Pelletier, DD Schmoyer, and WR Cannon. 2007. "SEBINI-CABIN: An Analysis Pipeline for Biological Network Inference, with a Case Study in Protein-Protein Interaction Network Reconstruction ." In Sixth International Conference on Machine Learning and Applications, (ICMLA 2007) , pp. 587-593.  IEEE Computer Society, Washington DC.  doi:10.1109/ICMLA.2007.63


  • Wang C., Zhang Y., McDermott J., and E. Barklis. 1993. Conditional infectivity of a human immunodeficiency virus matrix domain deletion mutant. J. Virol. 67(12):7067-7076
  • McDermott J., Farrell L., Ross R. and E. Barklis. 1996. Structural analysis of human immunodeficiency virus type 1 Gag protein interactions, using cysteine-specific reagents. J. Virol. 70(8):5106-5114
  • Barklis E.*, McDermott J.*, Wilkens S.*, Schabtach E., Capaldi R.A., Schmid M.F., Fuller S., Karanjia S., Love Z., Jones R., Rui Y., and D. Thompson,*. 1997. Structural analysis of membrane-bound retrovirus capsid proteins. EMBO 16:1199-1213. *Authors contributed equally to this work.
  • Barklis E., McDermott J., Wilkens S., Fuller S. and Thompson D. 1998. Organization of HIV-1 capsid proteins on a lipid monolayer. J. Biol. Chem. 273(13):7177-7180
  • Zuber G., McDermott J., Karanjia S., Zhao W., Schmid M.F., and E. Barklis. 2000. Assembly of retrovirus capsid-nucleocapsid proteins in the presence of membranes or RNA. J. Virol. 74(6): 7431-41
  • McDermott J., Karanjia, S., Love Z., and E. Barklis. 2000. Crosslink analysis of N-terminal, C-terminal, and N/B determining regions of Moloney murine leukemia virus capsid protein. Virology 269: 190-200
  • McDermott J., Mayo K., and E. Barklis. 2000. Three-dimensional organization of retroviral capsid proteins on a lipid monolayer. J. Mol. Biol. 302:121-33
  • Mayo K., Vana M.L., McDermott, J., Huseby, D., Leis, J. and E. Barklis. 2002. Analysis of Rous sarcoma virus capsid protein variants assembled on lipid monolayers. J. Mol. Biol. 316:667-678
  • Mayo K., McDermott, J., E. Barklis. 2002. Hexagonal organization of Moloney murine leukemia virus capsid proteins. Virology. 298:30-38.
  • Barklis E., and J. McDermott.2002. EMXtalOrg: An EM tilt data organization and processing suite. Ultramicroscopy. 93(1):11-17.
  • Mayo K., Huseby D., McDermott J., Arvidson B., Finlay L. and E. Barklis. 2003. Retrovirus capsid protein assembly arrangements. J. Mol. Biol. 325:225-37
  • McDermott J.and R. Samudrala. 2003. Bioverse: functional, structural and contextual annotation of proteins and proteomes. NAR 31:3736-7.
  • McDermott J.and R. Samudrala. 2004. Enhanced functional information from predicted protein networks. Trends Biotechnology 22(2):60-62
  • Chang AN, McDermott J.and R. Samudrala. 2005. An enhanced Java graph applet interface for visualizing interactomes. Bioinformatics 21(8):1741-2.
  • McDermott J.and R. Samudrala. 2005. Functional annotation from predicted protein interaction networks. Bioinformatics 21(15):3217-26.
  • McDermott J., Guerquin M., Frazier Z., Chang AN, and R. Samudrala. 2005. BIOVERSE: Enhancements to the framework for structural, functional, and contextual modeling of proteins and proteomes. Nucleic Acids Research 33:W324-325.
  • Wang W, Zheng H, Yang S, Yu H, Li J, Jiang H, Su J, Yang L, Zhang J, McDermott J., Samudrala R, Wang J, Yang H, Yu J, Kristiansen K, Wong GK, and J. Wang. 2005. Origin and evolution of new exons in rodents. Genome Research 15(9):1258-64.
  • J. Yu, J. Wang, W. Lin, S. Li, H. Li, J. Zhou, P. Ni, W. Dong, S. Hu, C. Zeng, J. Zhang, Y. Zhang, R. Li, Z. Xu, X. Li, H. Zheng, L. Cong, L. Lin, J. Yin, J. Geng, G. Li, J. Shi, J. Liu, H. Lv, J. Li, Y. Deng, L. Ran, X. Shi, X. Wang, Q. Wu, C. Li, X. Ren, D. Li, D. Liu, X. Zhang, Z. Ji, W. Zhao, Y. Sun, Z. Zhang, J. Bao, Y. Han, L. Dong, J. Ji, P. Chen, S. Wu, Y. Xiao, D. Bu, J. Tan, L. Yang, C. Ye, J. Xu, Y. Zhou, Y. Yu, B. Zhang, S. Zhuang, H. Wei, B. Liu, M. Lei, H. Yu, Y. Li, H. Xu, S. Wei, X. He, L. Fang, X. Huang, Z. Su, W. Tong, Z. Tong, J. Ye, L. Wang, T. Lei, C. Chen, H. Chen, H. Huang, F. Zhang, N. Li, C. Zhao, Y. Huang, L. Li, Y. Xi, Q. Qi, W. Li, W. Hu, X. Tian, Y. Jiao, X. Liang, J. Jin, L. Gao, W. Zheng, B. Hao, S. Liu, W. Wang, L. Yuan, M. Cao, J. McDermott, R. Samudrala, G. K. Wong and H. Yang. 2005. The Genomes of Oryza sativa: A History of Duplications. PLoS Biol 2005, 3(2):e38.
  • Chang AN., McDermott J., Frazier Z., Guerquin M., and R. Samudrala. 2006. Integrator: Interactive graphical search of large protein interactomes over the web. BMC Bioinformatics. 7:146
| Pacific Northwest National Laboratory